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LANDFIRE Map Units Integration for Enhanced Fire Ecology Understanding

This project aims to develop detailed map units for all lands with repeatable, scalable, and model-able features to improve vegetation classification and fire behavior modeling. The focus is on integrating existing vegetation structures, biophysical settings, historical fire data, and fuel models for accurate mapping and analysis. The project includes map unit requirements, vegetation layers, and mapping fuels using remote sensing, GIS, and biophysical modeling methods.

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LANDFIRE Map Units Integration for Enhanced Fire Ecology Understanding

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  1. Map Units for LANDFIRE:Integrating Vegetation Classification and Map Legends

  2. LANDFIRE DELIVERABLES VEGETATION Existing vegetation composition Existing vegetation structure Biophysical Settings FIRE ECOLOGY Layers Historical fire return interval Historical fire severity Historical fire regime Current Succession Class Vegetation departure Fire Regime Condition Classes FIRE BEHAVIOR/FIRE EFFECTS Layers Fire behavior fuel models Canopy bulk density Canopy base height Canopy cover Canopy height FCC Fuelbeds Fuel Loading Models

  3. LANDFIRE DELIVERABLES VEGETATION Existing vegetation composition Existing vegetation structure Biophysical Settings FIRE BEHAVIOR/FIRE EFFECTS Fire behavior fuel models Canopy bulk density Canopy base height Canopy cover Canopy height FCC Fuelbeds Fuel Loading Models FIRE ECOLOGY Historical fire return interval Historical fire severity Historical fire regime Current Succession Class Vegetation departure Fire Regime Condition Classes

  4. LANDFIRE Map Unit Development • All Lands & Vegetative Communities • Same level of detail • Forestlands, Shrublands, and Grasslands • Repeatable • Quick and affordable • Target Map Accuracies: • 60 to 80 percent map accuracy • Consistent for the Map Extent (National) • Map units mean the same thing in Florida as they do in Colorado

  5. Map Unit Requirements • Identifiable • from field or plot data • Map-able • 30 meter resolution • 60-80% accurate • Scalable • link with existing classifications • Model-able • provide required model inputs

  6. LANDFIRE Vegetation Layers Potential Vegetation Type (PVT) or Biophysical Setting (BpS) Existing Vegetation Type (Species Composition) Existing Structural Stage

  7. Existing Vegetation Type:Other Efforts Alliances and Associations of the USNVC (Grossman and others 1998) Sagebrush cover type map (SAGEMAP 2002) and classification (Reid and others 2002) developed by USGS Forest Cover Types of the United States and Canada, Society of American Foresters (Eyre 1980) Rangeland Cover Types of the United States, Society for Range Management (Shiflet 1994) GAP Cover Types for the eleven western states complied by the BLM

  8. Map Unit Requirements • Identifiable • from field or plot data • through dominance of species or groups of species on the plots • through individual or groups of indicator species on plots • dichotomous Field Key with “field and floristic criteria” • Sequence Table for plot data with “ floristic criteria”

  9. Sequence Tables • Criteria • Absolute cover for lifeforms • Relative cover for floristic criteria

  10. Sequence Tables • Criteria • Absolute cover for lifeforms • Relative cover for floristic criteria • Automation • BpS_EVT_Key_Classifier • Summaries by BpS, EVT, BpS/EVT • Constancy/Cover by BpS, EVT, BpS/EVT

  11. Map Unit Requirements • Map-able Final Cleanup Sequence Tables: • Mappers incorporate QA/QC for plots during mapping process and update MAT (contains training plots) • NatureServe runs through unclassified plot data and applies a qualitative classification • LFRDB determines what plot data is releasable and not releasable • Final MAT posted and available

  12. Map Unit Requirements • Scalable • Meet different scaling needs, fine to broad, by linking to existing classification; crosswalks • Maintain continuity between maps of different scales.

  13. Map Unit Requirements • Model-able • Provide “correct” combos for fuel lookup tables and inputs • Anomalous combinations of vegetation composition, structure and site potential will not have plot data and thus no associated fuels inputs

  14. Mapping Fuels for LANDFIRE:Integrating Remote Sensing, GIS, and Biophysical Modeling

  15. Why are Fuels Important?The one factor over which we have the most control

  16. Fuels MapsThe Most Important Fire Management LayerPotential Uses • Predict future growth of fire • Develop fire danger, hazard, risk layers • Plan future fires and prioritize treatments • Simulate fire effects-smoke, tree mortality • Evaluate management alternatives

  17. What Are Fuels? Live and dead biomass • Biomass when burned: • Contributes to fire propagation • Produces smoke • Generates heat to kill flora & fauna

  18. Challenges in Mapping Fuels • Canopy obstruction • Fuel bed diversity • Fire behavior fuel models • Fuel complexity • Fuel variability • Fine resolutions

  19. Fuel Bed DiversityMany categories of fuels Dead and Live Crown foliage and branchwood Arboreal Mosses and Lichens Live and Dead Tree Regeneration Live and Dead Shrub and Herbaceous Logs Downed Dead Woody Twig and Branchwood Litter and Duff Cones, Buds, Mosses, Lichens

  20. Fuel Complexity • Each fuel type important to one, but not all, fire applications • Fire behavior needs description of fine fuels • Smoke prediction requires description of all fuel types • Fuel models and fuel classifications must be robust

  21. Fuel Variability • Fuels are continuous not discrete • Highly variable in space and time • Related to many factors • Stand history • Biophysical setting • Community composition • Stand Structure

  22. Fuel Mapping Approaches • Field Reconnaissance • Remote Sensing

  23. Correlated with many ecosystem attributes Governs fuel dynamics Classifications available Species Composition Stand Structure Biophysical Setting Fuel Mapping Strategy

  24. Fuel Variability Example FBFM 9 - Pine Litter FBFM 2 - Conifer Grass FBFM 5 - Live Shrub

  25. Remote sensing These systems characterize the physical and chemical properties of atmospherically transmitted radiation. The reflected radiation is coupled with atmospheric models and fitted to geographic location, time and date to determine apparent surface reflectance. This remotely sensed data can be either directly or indirectly related to identifiable materials such as shade, various soils, non-photosynthetic vegetation, green biomass, live fuel moisture, diverse vegetation species and unique land-cover types.

  26. LANDFIRE Fuels Two major divisions of fuels are recognized by the LANDFIRE project – surface fuels and canopy fuels. • Surface fuelsare those biomass components that occur on the ground (less than six feet tall) and are the fuels that carry a surface fire. • Live or dead, herbaceous or shrub, downed dead woody, litter, and duff • Fire Behavior Fuel models have been developed to predict fire behavior. • Canopy fuelsare those aerial biomass components higher than six feet that can carry a crown fire and are usually consumed in the crown fire. • 1) Bulk density (kg m-3), • 2) Canopy cover (%), • 3) Canopy height (m), • 4) Canopy base height (m).

  27. FARSITE Input Layers Base Vegetation Layers Ancillary Layers

  28. METHODS • Creating the surface fuel maps • Create lookup tables for FBFM13 • Creating the surface fuel model maps from the lookup tables

  29. Fire Behavior Fuel Models • Describes expected fire behavior • Not a description of actual fuel conditions • Complicated procedure to construct models • Fuel model construction subjective • Assessment in field is subjective

  30. METHODS continued • Creating the canopy fuel maps • Calculate all four canopy characteristics for all plots in the LANDFIRE reference database with comprehensive tree data using the FUELCALC program • Classification and regression trees were used to link the calculated reference data to Landsat satellite imagery and a series of 30-meter, spatially-explicit gradient layers representing climate, fire ecology, soil, and topography.

  31. METHODS continued • Performing QA/QC procedures • Create fuels QA/QC ruleset • Check all layers for data gaps • Check all layers for logic inconsistencies within LANDFIRE layers • Performing accuracy assessment • Calculate accuracy of statistical models • Calculate classification accuracy of fuel model keys • Calculate pixel accuracy of fuel maps • Calculate mapping accuracy of fuel maps

  32. LANDFIRE Fuel Layers • Standard 13 Fire Behavior Fuel Models (FBFM13). • Canopy bulk density (CBD) • Canopy cover (CC) • Canopy height (CH) • Canopy base height (CBH)

  33. Fire Behavior Fuel Model

  34. Canopy Base Height

  35. Canopy Height

  36. Canopy Cover

  37. Crown Bulk Density

  38. LANDFIRE Fuel Layers • Standard 13 Fire Behavior Fuel Models (FBFM13). • Canopy bulk density (CBD) • Canopy cover (CC) • Canopy height (CH) • Canopy base height (CBH)

  39. LANDFIRE Fuel Layers • Standard 13 Fire Behavior Fuel Models (FBFM13). • Canopy bulk density (CBD) • Canopy cover (CC) • Canopy height (CH) • Canopy base height (CBH) plus: • New 40 Fire Behavior Fuel Models (FBFM40) • Fuel Characteristic Classification System (FCCS) • Fuel Loading Models (FLM)

  40. Other Analysis ToolsNew Fuel Models and Fuel Classifications New Fire behavior, Fire effects Fuel Models

  41. New set of 40 fire behavior fuel models (FBFM40) • The new set of 40 fire behavior fuel models (FBFM40) are hierarchically organized by fuel strata and fuel loading. • The 40 fuel models have already been implemented into the BEHAVE fire modeling system and the FARSITE fire growth model. • Subtle modifications in fuelbeds as a result of fuel treatment activities should be represented by these 40 fuel models.

  42. The FCCS Fuelbed concept was developed by the Fire and Environmental Research Applications (FERA) at PNW, Seattle. It includes complete descriptions of typical fuel situations around the nation. The FCCS summarizes fuel by component using canopy, ground, and surface fuel stratifications. LANDFIRE Prototype Zone 16 Fuel Characteristic Classification System (FCCS) National Fuelbed Map

  43. Questions???

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